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<title>OpenCV: cv::bioinspired::Retina Class Reference</title>
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<li class="navelem"><a class="el" href="../../d2/d75/namespacecv.html">cv</a></li><li class="navelem"><a class="el" href="../../d2/d81/namespacecv_1_1bioinspired.html">bioinspired</a></li><li class="navelem"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html">Retina</a></li>  </ul>
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<a href="#pub-methods">Public Member Functions</a> |
<a href="#pub-static-methods">Static Public Member Functions</a> |
<a href="../../dc/d47/classcv_1_1bioinspired_1_1Retina-members.html">List of all members</a>  </div>
  <div class="headertitle">
<div class="title">cv::bioinspired::Retina Class Reference<span class="mlabels"><span class="mlabel">abstract</span></span><div class="ingroups"><a class="el" href="../../dd/deb/group__bioinspired.html">Biologically inspired vision models and derivated tools</a></div></div>  </div>
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<p>class which allows the Gipsa/Listic Labs model to be used with OpenCV.  
 <a href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#details">More...</a></p>
<p><code>#include &lt;opencv2/bioinspired/retina.hpp&gt;</code></p>
<div class="dynheader">
Inheritance diagram for cv::bioinspired::Retina:</div>
<div class="dyncontent">
 <div class="center">
  <img alt="" src="../../dc/d54/classcv_1_1bioinspired_1_1Retina.png" usemap="#cv::bioinspired::Retina_map"/>
  <map id="cv::bioinspired::Retina_map" name="cv::bioinspired::Retina_map">
<area alt="cv::Algorithm" coords="0,0,135,24" href="../../d3/d46/classcv_1_1Algorithm.html" shape="rect" title="This is a base class for all more or less complex algorithms in OpenCV. "/>
</map>
 </div></div>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:a1e109acc73714943702572866487965b"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a1e109acc73714943702572866487965b">activateContoursProcessing</a> (const bool activate)=0</td></tr>
<tr class="memdesc:a1e109acc73714943702572866487965b"><td class="mdescLeft"> </td><td class="mdescRight">Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated.  <a href="#a1e109acc73714943702572866487965b">More...</a><br/></td></tr>
<tr class="separator:a1e109acc73714943702572866487965b"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:afe65e21f82b421cf468e225b3cd61322"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#afe65e21f82b421cf468e225b3cd61322">activateMovingContoursProcessing</a> (const bool activate)=0</td></tr>
<tr class="memdesc:afe65e21f82b421cf468e225b3cd61322"><td class="mdescLeft"> </td><td class="mdescRight">Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated.  <a href="#afe65e21f82b421cf468e225b3cd61322">More...</a><br/></td></tr>
<tr class="separator:afe65e21f82b421cf468e225b3cd61322"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a1bb2ed3bee0ced414ed0533fba641dec"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a1bb2ed3bee0ced414ed0533fba641dec">applyFastToneMapping</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> inputImage, <a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> outputToneMappedImage)=0</td></tr>
<tr class="memdesc:a1bb2ed3bee0ced414ed0533fba641dec"><td class="mdescLeft"> </td><td class="mdescRight">Method which processes an image in the aim to correct its luminance correct backlight problems, enhance details in shadows.  <a href="#a1bb2ed3bee0ced414ed0533fba641dec">More...</a><br/></td></tr>
<tr class="separator:a1bb2ed3bee0ced414ed0533fba641dec"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a09603d1ed6c8f82459526bbe2ac4eac6"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a09603d1ed6c8f82459526bbe2ac4eac6">clearBuffers</a> ()=0</td></tr>
<tr class="memdesc:a09603d1ed6c8f82459526bbe2ac4eac6"><td class="mdescLeft"> </td><td class="mdescRight">Clears all retina buffers.  <a href="#a09603d1ed6c8f82459526bbe2ac4eac6">More...</a><br/></td></tr>
<tr class="separator:a09603d1ed6c8f82459526bbe2ac4eac6"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a9266e82cc8de64595687f9dce2b47f87"><td align="right" class="memItemLeft" valign="top">virtual <a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a9266e82cc8de64595687f9dce2b47f87">getInputSize</a> ()=0</td></tr>
<tr class="memdesc:a9266e82cc8de64595687f9dce2b47f87"><td class="mdescLeft"> </td><td class="mdescRight">Retreive retina input buffer size.  <a href="#a9266e82cc8de64595687f9dce2b47f87">More...</a><br/></td></tr>
<tr class="separator:a9266e82cc8de64595687f9dce2b47f87"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad8ec45e39a333eeb759e0925357f4ec5"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#ad8ec45e39a333eeb759e0925357f4ec5">getMagno</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> retinaOutput_magno)=0</td></tr>
<tr class="memdesc:ad8ec45e39a333eeb759e0925357f4ec5"><td class="mdescLeft"> </td><td class="mdescRight">Accessor of the motion channel of the retina (models peripheral vision).  <a href="#ad8ec45e39a333eeb759e0925357f4ec5">More...</a><br/></td></tr>
<tr class="separator:ad8ec45e39a333eeb759e0925357f4ec5"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a33590324368a1f1140dc68faf8049fca"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a33590324368a1f1140dc68faf8049fca">getMagnoRAW</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> retinaOutput_magno)=0</td></tr>
<tr class="memdesc:a33590324368a1f1140dc68faf8049fca"><td class="mdescLeft"> </td><td class="mdescRight">Accessor of the motion channel of the retina (models peripheral vision).  <a href="#a33590324368a1f1140dc68faf8049fca">More...</a><br/></td></tr>
<tr class="separator:a33590324368a1f1140dc68faf8049fca"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a5185329f03228f9427481afaff0e29bb"><td align="right" class="memItemLeft" valign="top">virtual const <a class="el" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a5185329f03228f9427481afaff0e29bb">getMagnoRAW</a> () const =0</td></tr>
<tr class="separator:a5185329f03228f9427481afaff0e29bb"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a1a6a151832812c2b276e5cb244f7a544"><td align="right" class="memItemLeft" valign="top">virtual <a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a1a6a151832812c2b276e5cb244f7a544">getOutputSize</a> ()=0</td></tr>
<tr class="memdesc:a1a6a151832812c2b276e5cb244f7a544"><td class="mdescLeft"> </td><td class="mdescRight">Retreive retina output buffer size that can be different from the input if a spatial log transformation is applied.  <a href="#a1a6a151832812c2b276e5cb244f7a544">More...</a><br/></td></tr>
<tr class="separator:a1a6a151832812c2b276e5cb244f7a544"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ada6dac13985015a01a461b5cde177e95"><td align="right" class="memItemLeft" valign="top">virtual <a class="el" href="../../d2/df5/structcv_1_1bioinspired_1_1RetinaParameters.html">RetinaParameters</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#ada6dac13985015a01a461b5cde177e95">getParameters</a> ()=0</td></tr>
<tr class="separator:ada6dac13985015a01a461b5cde177e95"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a89bbd0119f52b9936cabdfba97561c0f"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a89bbd0119f52b9936cabdfba97561c0f">getParvo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> retinaOutput_parvo)=0</td></tr>
<tr class="memdesc:a89bbd0119f52b9936cabdfba97561c0f"><td class="mdescLeft"> </td><td class="mdescRight">Accessor of the details channel of the retina (models foveal vision).  <a href="#a89bbd0119f52b9936cabdfba97561c0f">More...</a><br/></td></tr>
<tr class="separator:a89bbd0119f52b9936cabdfba97561c0f"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab8bb17543b78ef9d32be3a4619d2b2dd"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#ab8bb17543b78ef9d32be3a4619d2b2dd">getParvoRAW</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> retinaOutput_parvo)=0</td></tr>
<tr class="memdesc:ab8bb17543b78ef9d32be3a4619d2b2dd"><td class="mdescLeft"> </td><td class="mdescRight">Accessor of the details channel of the retina (models foveal vision).  <a href="#ab8bb17543b78ef9d32be3a4619d2b2dd">More...</a><br/></td></tr>
<tr class="separator:ab8bb17543b78ef9d32be3a4619d2b2dd"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a12f3b934dc029c81d733007b27322534"><td align="right" class="memItemLeft" valign="top">virtual const <a class="el" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a12f3b934dc029c81d733007b27322534">getParvoRAW</a> () const =0</td></tr>
<tr class="separator:a12f3b934dc029c81d733007b27322534"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a80d39a3463c206425e16ce85caa78d03"><td align="right" class="memItemLeft" valign="top">virtual const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a80d39a3463c206425e16ce85caa78d03">printSetup</a> ()=0</td></tr>
<tr class="memdesc:a80d39a3463c206425e16ce85caa78d03"><td class="mdescLeft"> </td><td class="mdescRight">Outputs a string showing the used parameters setup.  <a href="#a80d39a3463c206425e16ce85caa78d03">More...</a><br/></td></tr>
<tr class="separator:a80d39a3463c206425e16ce85caa78d03"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a9d18358b520c4dd7931a9154cc053649"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a9d18358b520c4dd7931a9154cc053649">run</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> inputImage)=0</td></tr>
<tr class="memdesc:a9d18358b520c4dd7931a9154cc053649"><td class="mdescLeft"> </td><td class="mdescRight">Method which allows retina to be applied on an input image,.  <a href="#a9d18358b520c4dd7931a9154cc053649">More...</a><br/></td></tr>
<tr class="separator:a9d18358b520c4dd7931a9154cc053649"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aa66dca22cadf9293164bef39f3690a94"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#aa66dca22cadf9293164bef39f3690a94">setColorSaturation</a> (const bool saturateColors=true, const float colorSaturationValue=4.0f)=0</td></tr>
<tr class="memdesc:aa66dca22cadf9293164bef39f3690a94"><td class="mdescLeft"> </td><td class="mdescRight">Activate color saturation as the final step of the color demultiplexing process -&gt; this saturation is a sigmoide function applied to each channel of the demultiplexed image.  <a href="#aa66dca22cadf9293164bef39f3690a94">More...</a><br/></td></tr>
<tr class="separator:aa66dca22cadf9293164bef39f3690a94"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a741fc44059111f3e2d5ba6ab1fa1d907"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a741fc44059111f3e2d5ba6ab1fa1d907">setup</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> retinaParameterFile="", const bool applyDefaultSetupOnFailure=true)=0</td></tr>
<tr class="memdesc:a741fc44059111f3e2d5ba6ab1fa1d907"><td class="mdescLeft"> </td><td class="mdescRight">Try to open an XML retina parameters file to adjust current retina instance setup.  <a href="#a741fc44059111f3e2d5ba6ab1fa1d907">More...</a><br/></td></tr>
<tr class="separator:a741fc44059111f3e2d5ba6ab1fa1d907"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a75ee531b20e2c32892773625de5ecdb1"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a75ee531b20e2c32892773625de5ecdb1">setup</a> (<a class="el" href="../../da/d56/classcv_1_1FileStorage.html">cv::FileStorage</a> &amp;fs, const bool applyDefaultSetupOnFailure=true)=0</td></tr>
<tr class="separator:a75ee531b20e2c32892773625de5ecdb1"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ac9f944965a104c355467628b07eaf887"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#ac9f944965a104c355467628b07eaf887">setup</a> (<a class="el" href="../../d2/df5/structcv_1_1bioinspired_1_1RetinaParameters.html">RetinaParameters</a> newParameters)=0</td></tr>
<tr class="separator:ac9f944965a104c355467628b07eaf887"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:acfec2a2bef33e6ef73a38576f645278b"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#acfec2a2bef33e6ef73a38576f645278b">setupIPLMagnoChannel</a> (const bool normaliseOutput=true, const float parasolCells_beta=0.f, const float parasolCells_tau=0.f, const float parasolCells_k=7.f, const float amacrinCellsTemporalCutFrequency=1.2f, const float V0CompressionParameter=0.95f, const float localAdaptintegration_tau=0.f, const float localAdaptintegration_k=7.f)=0</td></tr>
<tr class="memdesc:acfec2a2bef33e6ef73a38576f645278b"><td class="mdescLeft"> </td><td class="mdescRight">Set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel.  <a href="#acfec2a2bef33e6ef73a38576f645278b">More...</a><br/></td></tr>
<tr class="separator:acfec2a2bef33e6ef73a38576f645278b"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ac6d6767e14212b5ebd7c5bbc6477fa7a"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#ac6d6767e14212b5ebd7c5bbc6477fa7a">setupOPLandIPLParvoChannel</a> (const bool colorMode=true, const bool normaliseOutput=true, const float photoreceptorsLocalAdaptationSensitivity=0.7f, const float photoreceptorsTemporalConstant=0.5f, const float photoreceptorsSpatialConstant=0.53f, const float horizontalCellsGain=0.f, const float HcellsTemporalConstant=1.f, const float HcellsSpatialConstant=7.f, const float ganglionCellsSensitivity=0.7f)=0</td></tr>
<tr class="memdesc:ac6d6767e14212b5ebd7c5bbc6477fa7a"><td class="mdescLeft"> </td><td class="mdescRight">Setup the OPL and IPL parvo channels (see biologocal model)  <a href="#ac6d6767e14212b5ebd7c5bbc6477fa7a">More...</a><br/></td></tr>
<tr class="separator:ac6d6767e14212b5ebd7c5bbc6477fa7a"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a92d80a2c309c46a46b22ec125cad3943"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a92d80a2c309c46a46b22ec125cad3943">write</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> fs) const =0</td></tr>
<tr class="memdesc:a92d80a2c309c46a46b22ec125cad3943"><td class="mdescLeft"> </td><td class="mdescRight">Write xml/yml formated parameters information.  <a href="#a92d80a2c309c46a46b22ec125cad3943">More...</a><br/></td></tr>
<tr class="separator:a92d80a2c309c46a46b22ec125cad3943"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:af0fb1fda44face9993785ef41b38430d"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#af0fb1fda44face9993785ef41b38430d">write</a> (<a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &amp;fs) const <a class="el" href="../../db/de0/group__core__utils.html#ga4d89d63e402ef9ddc48e18e21180fe4a">CV_OVERRIDE</a>=0</td></tr>
<tr class="separator:af0fb1fda44face9993785ef41b38430d"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pub_methods_classcv_1_1Algorithm"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classcv_1_1Algorithm')"><img alt="-" src="../../closed.png"/> Public Member Functions inherited from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html">cv::Algorithm</a></td></tr>
<tr class="memitem:a827c8b2781ed17574805f373e6054ff1 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a827c8b2781ed17574805f373e6054ff1">Algorithm</a> ()</td></tr>
<tr class="separator:a827c8b2781ed17574805f373e6054ff1 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a8ae826127fa0f1f8d10a24841bd376f8 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a8ae826127fa0f1f8d10a24841bd376f8">~Algorithm</a> ()</td></tr>
<tr class="separator:a8ae826127fa0f1f8d10a24841bd376f8 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aec9c965448e4dc851d7cacd3abd84cd1 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#aec9c965448e4dc851d7cacd3abd84cd1">clear</a> ()</td></tr>
<tr class="memdesc:aec9c965448e4dc851d7cacd3abd84cd1 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Clears the algorithm state.  <a href="../../d3/d46/classcv_1_1Algorithm.html#aec9c965448e4dc851d7cacd3abd84cd1">More...</a><br/></td></tr>
<tr class="separator:aec9c965448e4dc851d7cacd3abd84cd1 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab6a18f1825475643e94381697d413972 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#ab6a18f1825475643e94381697d413972">empty</a> () const</td></tr>
<tr class="memdesc:ab6a18f1825475643e94381697d413972 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Returns true if the <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html" title="This is a base class for all more or less complex algorithms in OpenCV. ">Algorithm</a> is empty (e.g. in the very beginning or after unsuccessful read.  <a href="../../d3/d46/classcv_1_1Algorithm.html#ab6a18f1825475643e94381697d413972">More...</a><br/></td></tr>
<tr class="separator:ab6a18f1825475643e94381697d413972 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a286fc82744ccab3d248aca44524266a9 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a286fc82744ccab3d248aca44524266a9">getDefaultName</a> () const</td></tr>
<tr class="separator:a286fc82744ccab3d248aca44524266a9 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aef2ad3f4145bd6e8c3664eb1c4b5e1e6 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#aef2ad3f4145bd6e8c3664eb1c4b5e1e6">read</a> (const <a class="el" href="../../de/dd9/classcv_1_1FileNode.html">FileNode</a> &amp;fn)</td></tr>
<tr class="memdesc:aef2ad3f4145bd6e8c3664eb1c4b5e1e6 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Reads algorithm parameters from a file storage.  <a href="../../d3/d46/classcv_1_1Algorithm.html#aef2ad3f4145bd6e8c3664eb1c4b5e1e6">More...</a><br/></td></tr>
<tr class="separator:aef2ad3f4145bd6e8c3664eb1c4b5e1e6 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a0a880744bc4e3f45711444571df47d67 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a0a880744bc4e3f45711444571df47d67">save</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;filename) const</td></tr>
<tr class="separator:a0a880744bc4e3f45711444571df47d67 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a763a62d1b03042eef7d7fc3ac6c87c79 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a763a62d1b03042eef7d7fc3ac6c87c79">write</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &gt; &amp;fs, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;name=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>()) const</td></tr>
<tr class="memdesc:a763a62d1b03042eef7d7fc3ac6c87c79 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a763a62d1b03042eef7d7fc3ac6c87c79">More...</a><br/></td></tr>
<tr class="separator:a763a62d1b03042eef7d7fc3ac6c87c79 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr class="memitem:a5089c21c98da9e7ccf0a6896e7d6a400"><td align="right" class="memItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html">Retina</a> &gt; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a5089c21c98da9e7ccf0a6896e7d6a400">create</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> inputSize)</td></tr>
<tr class="separator:a5089c21c98da9e7ccf0a6896e7d6a400"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a996e8169ed7b9152deff4a0c0c5ae1a6"><td align="right" class="memItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html">Retina</a> &gt; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a996e8169ed7b9152deff4a0c0c5ae1a6">create</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> inputSize, const bool colorMode, int colorSamplingMethod=<a class="el" href="../../dd/deb/group__bioinspired.html#gga9960117097f8d8ba20bafa0098ea20d1aaadeb7c2a3a68e14d700f15ed4323b62">RETINA_COLOR_BAYER</a>, const bool useRetinaLogSampling=false, const float reductionFactor=1.0f, const float samplingStrength=10.0f)</td></tr>
<tr class="memdesc:a996e8169ed7b9152deff4a0c0c5ae1a6"><td class="mdescLeft"> </td><td class="mdescRight">Constructors from standardized interfaces : retreive a smart pointer to a <a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html" title="class which allows the Gipsa/Listic Labs model to be used with OpenCV. ">Retina</a> instance.  <a href="#a996e8169ed7b9152deff4a0c0c5ae1a6">More...</a><br/></td></tr>
<tr class="separator:a996e8169ed7b9152deff4a0c0c5ae1a6"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pub_static_methods_classcv_1_1Algorithm"><td colspan="2" onclick="javascript:toggleInherit('pub_static_methods_classcv_1_1Algorithm')"><img alt="-" src="../../closed.png"/> Static Public Member Functions inherited from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html">cv::Algorithm</a></td></tr>
<tr class="memitem:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a623841c33b58ea9c4847da04607e067b">load</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;filename, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;objname=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>())</td></tr>
<tr class="memdesc:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Loads algorithm from the file.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a623841c33b58ea9c4847da04607e067b">More...</a><br/></td></tr>
<tr class="separator:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a3ba305a10d02479c13cf7d169c321547">loadFromString</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;strModel, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;objname=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>())</td></tr>
<tr class="memdesc:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Loads algorithm from a String.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a3ba305a10d02479c13cf7d169c321547">More...</a><br/></td></tr>
<tr class="separator:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#ad8c591bacb34c485f5b7a250c314fc53">read</a> (const <a class="el" href="../../de/dd9/classcv_1_1FileNode.html">FileNode</a> &amp;fn)</td></tr>
<tr class="memdesc:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Reads algorithm from the file node.  <a href="../../d3/d46/classcv_1_1Algorithm.html#ad8c591bacb34c485f5b7a250c314fc53">More...</a><br/></td></tr>
<tr class="separator:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="inherited"></a>
Additional Inherited Members</h2></td></tr>
<tr class="inherit_header pro_methods_classcv_1_1Algorithm"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classcv_1_1Algorithm')"><img alt="-" src="../../closed.png"/> Protected Member Functions inherited from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html">cv::Algorithm</a></td></tr>
<tr class="memitem:a68eeca71617474ad3d4561786f0289d2 inherit pro_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a68eeca71617474ad3d4561786f0289d2">writeFormat</a> (<a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &amp;fs) const</td></tr>
<tr class="separator:a68eeca71617474ad3d4561786f0289d2 inherit pro_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<a id="details" name="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>class which allows the Gipsa/Listic Labs model to be used with OpenCV. </p>
<p>This retina model allows spatio-temporal image processing (applied on still images, video sequences). As a summary, these are the retina model properties:</p><ul>
<li>It applies a spectral whithening (mid-frequency details enhancement)</li>
<li>high frequency spatio-temporal noise reduction</li>
<li>low frequency luminance to be reduced (luminance range compression)</li>
<li>local logarithmic luminance compression allows details to be enhanced in low light conditions</li>
</ul>
<p>USE : this model can be used basically for spatio-temporal video effects but also for : _using the getParvo method output matrix : texture analysiswith enhanced signal to noise ratio and enhanced details robust against input images luminance ranges _using the getMagno method output matrix : motion analysis also with the previously cited properties</p>
<p>for more information, reer to the following papers : Benoit A., Caplier A., Durette B., Herault, J., "USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING", Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: <a href="http://dx.doi.org/10.1016/j.cviu.2010.01.011">http://dx.doi.org/10.1016/j.cviu.2010.01.011</a> Vision: Images, Signals and Neural Networks: Models of Neural Processing in Visual Perception (Progress in Neural Processing),By: Jeanny Herault, ISBN: 9814273686. WAPI (Tower ID): 113266891.</p>
<p>The retina filter includes the research contributions of phd/research collegues from which code has been redrawn by the author : take a look at the retinacolor.hpp module to discover Brice Chaix de Lavarene color mosaicing/demosaicing and the reference paper: B. Chaix de Lavarene, D. Alleysson, B. Durette, J. Herault (2007). "Efficient demosaicing through recursive filtering", IEEE International Conference on Image Processing ICIP 2007 take a look at imagelogpolprojection.hpp to discover retina spatial log sampling which originates from Barthelemy Durette phd with Jeanny Herault. A <a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html" title="class which allows the Gipsa/Listic Labs model to be used with OpenCV. ">Retina</a> / V1 cortex projection is also proposed and originates from Jeanny's discussions. more informations in the above cited Jeanny Heraults's book. </p>
</div><h2 class="groupheader">Member Function Documentation</h2>
<a id="a1e109acc73714943702572866487965b"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a1e109acc73714943702572866487965b">◆ </a></span>activateContoursProcessing()</h2>
<div class="memitem">
<div class="memproto">
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  <td class="mlabels-left">
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          <td class="memname">virtual void cv::bioinspired::Retina::activateContoursProcessing </td>
          <td>(</td>
          <td class="paramtype">const bool </td>
          <td class="paramname"><em>activate</em></td><td>)</td>
          <td></td>
        </tr>
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  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.bioinspired_Retina.activateContoursProcessing(</td><td class="paramname">activate</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">activate</td><td>true if Parvocellular (contours information extraction) output should be activated, false if not... if activated, the Parvocellular output can be retrieved using the <a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a89bbd0119f52b9936cabdfba97561c0f" title="Accessor of the details channel of the retina (models foveal vision). ">Retina::getParvo</a> methods </td></tr>
  </table>
  </dd>
</dl>
</div>
</div>
<a id="afe65e21f82b421cf468e225b3cd61322"></a>
<h2 class="memtitle"><span class="permalink"><a href="#afe65e21f82b421cf468e225b3cd61322">◆ </a></span>activateMovingContoursProcessing()</h2>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
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  <td class="mlabels-left">
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          <td class="memname">virtual void cv::bioinspired::Retina::activateMovingContoursProcessing </td>
          <td>(</td>
          <td class="paramtype">const bool </td>
          <td class="paramname"><em>activate</em></td><td>)</td>
          <td></td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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<p>Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">activate</td><td>true if Magnocellular output should be activated, false if not... if activated, the Magnocellular output can be retrieved using the <b>getMagno</b> methods </td></tr>
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  </dd>
</dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a1bb2ed3bee0ced414ed0533fba641dec">◆ </a></span>applyFastToneMapping()</h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::applyFastToneMapping </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>inputImage</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>outputToneMappedImage</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>outputToneMappedImage</td><td>=</td><td>cv.bioinspired_Retina.applyFastToneMapping(</td><td class="paramname">inputImage[, outputToneMappedImage]</td><td>)</td></tr></table>
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<p>Method which processes an image in the aim to correct its luminance correct backlight problems, enhance details in shadows. </p>
<p>This method is designed to perform High Dynamic <a class="el" href="../../da/d35/classcv_1_1Range.html" title="Template class specifying a continuous subsequence (slice) of a sequence. ">Range</a> image tone mapping (compress &gt;8bit/pixel images to 8bit/pixel). This is a simplified version of the <a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html" title="class which allows the Gipsa/Listic Labs model to be used with OpenCV. ">Retina</a> Parvocellular model (simplified version of the run/getParvo methods call) since it does not include the spatio-temporal filter modelling the Outer Plexiform Layer of the retina that performs spectral whitening and many other stuff. However, it works great for tone mapping and in a faster way.</p>
<p>Check the demos and experiments section to see examples and the way to perform tone mapping using the original retina model and the method.</p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">inputImage</td><td>the input image to process (should be coded in float format : CV_32F, CV_32FC1, CV_32F_C3, CV_32F_C4, the 4th channel won't be considered). </td></tr>
    <tr><td class="paramname">outputToneMappedImage</td><td>the output 8bit/channel tone mapped image (CV_8U or CV_8UC3 format). </td></tr>
  </table>
  </dd>
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<h2 class="memtitle"><span class="permalink"><a href="#a09603d1ed6c8f82459526bbe2ac4eac6">◆ </a></span>clearBuffers()</h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::clearBuffers </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.bioinspired_Retina.clearBuffers(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>Clears all retina buffers. </p>
<p>(equivalent to opening the eyes after a long period of eye close ;o) whatchout the temporal transition occuring just after this method call. </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a5089c21c98da9e7ccf0a6896e7d6a400">◆ </a></span>create() <span class="overload">[1/2]</span></h2>
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          <td class="memname">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt;<a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html">Retina</a>&gt; cv::bioinspired::Retina::create </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> </td>
          <td class="paramname"><em>inputSize</em></td><td>)</td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.bioinspired.Retina_create(</td><td class="paramname">inputSize</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.bioinspired.Retina_create(</td><td class="paramname">inputSize, colorMode[, colorSamplingMethod[, useRetinaLogSampling[, reductionFactor[, samplingStrength]]]]</td><td>)</td></tr></table>
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<p>This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a996e8169ed7b9152deff4a0c0c5ae1a6">◆ </a></span>create() <span class="overload">[2/2]</span></h2>
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          <td class="memname">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt;<a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html">Retina</a>&gt; cv::bioinspired::Retina::create </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> </td>
          <td class="paramname"><em>inputSize</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const bool </td>
          <td class="paramname"><em>colorMode</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>colorSamplingMethod</em> = <code><a class="el" href="../../dd/deb/group__bioinspired.html#gga9960117097f8d8ba20bafa0098ea20d1aaadeb7c2a3a68e14d700f15ed4323b62">RETINA_COLOR_BAYER</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const bool </td>
          <td class="paramname"><em>useRetinaLogSampling</em> = <code>false</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>reductionFactor</em> = <code>1.0f</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>samplingStrength</em> = <code>10.0f</code> </td>
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          <td></td>
          <td>)</td>
          <td></td><td></td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.bioinspired.Retina_create(</td><td class="paramname">inputSize</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.bioinspired.Retina_create(</td><td class="paramname">inputSize, colorMode[, colorSamplingMethod[, useRetinaLogSampling[, reductionFactor[, samplingStrength]]]]</td><td>)</td></tr></table>
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<p>Constructors from standardized interfaces : retreive a smart pointer to a <a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html" title="class which allows the Gipsa/Listic Labs model to be used with OpenCV. ">Retina</a> instance. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">inputSize</td><td>the input frame size </td></tr>
    <tr><td class="paramname">colorMode</td><td>the chosen processing mode : with or without color processing </td></tr>
    <tr><td class="paramname">colorSamplingMethod</td><td>specifies which kind of color sampling will be used :<ul>
<li><a class="el" href="../../dd/deb/group__bioinspired.html#gga9960117097f8d8ba20bafa0098ea20d1a3e546a6616bc41d88f973691f6a22388" title="each pixel position is either R, G or B in a random choice ">cv::bioinspired::RETINA_COLOR_RANDOM</a>: each pixel position is either R, G or B in a random choice</li>
<li><a class="el" href="../../dd/deb/group__bioinspired.html#gga9960117097f8d8ba20bafa0098ea20d1acde9495f290217652b4d82f07f4a18c5" title="color sampling is RGBRGBRGB..., line 2 BRGBRGBRG..., line 3, GBRGBRGBR... ">cv::bioinspired::RETINA_COLOR_DIAGONAL</a>: color sampling is RGBRGBRGB..., line 2 BRGBRGBRG..., line 3, GBRGBRGBR...</li>
<li><a class="el" href="../../dd/deb/group__bioinspired.html#gga9960117097f8d8ba20bafa0098ea20d1aaadeb7c2a3a68e14d700f15ed4323b62" title="standard bayer sampling ">cv::bioinspired::RETINA_COLOR_BAYER</a>: standard bayer sampling </li>
</ul>
</td></tr>
    <tr><td class="paramname">useRetinaLogSampling</td><td>activate retina log sampling, if true, the 2 following parameters can be used </td></tr>
    <tr><td class="paramname">reductionFactor</td><td>only usefull if param useRetinaLogSampling=true, specifies the reduction factor of the output frame (as the center (fovea) is high resolution and corners can be underscaled, then a reduction of the output is allowed without precision leak </td></tr>
    <tr><td class="paramname">samplingStrength</td><td>only usefull if param useRetinaLogSampling=true, specifies the strength of the log scale that is applied </td></tr>
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<h2 class="memtitle"><span class="permalink"><a href="#a9266e82cc8de64595687f9dce2b47f87">◆ </a></span>getInputSize()</h2>
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          <td class="memname">virtual <a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> cv::bioinspired::Retina::getInputSize </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
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<p>Retreive retina input buffer size. </p>
<dl class="section return"><dt>Returns</dt><dd>the retina input buffer size </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#ad8ec45e39a333eeb759e0925357f4ec5">◆ </a></span>getMagno()</h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::getMagno </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>retinaOutput_magno</em></td><td>)</td>
          <td></td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retinaOutput_magno</td><td>=</td><td>cv.bioinspired_Retina.getMagno(</td><td class="paramname">[, retinaOutput_magno]</td><td>)</td></tr></table>
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<p>Accessor of the motion channel of the retina (models peripheral vision). </p>
<p>Warning, getMagnoRAW methods return buffers that are not rescaled within range [0;255] while the non RAW method allows a normalized matrix to be retrieved. </p><dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">retinaOutput_magno</td><td>the output buffer (reallocated if necessary), format can be :<ul>
<li>a <a class="el" href="../../d3/d63/classcv_1_1Mat.html" title="n-dimensional dense array class ">Mat</a>, this output is rescaled for standard 8bits image processing use in OpenCV</li>
<li>RAW methods actually return a 1D matrix (encoding is M1, M2,... Mn), this output is the original retina filter model output, without any quantification or rescaling. </li>
</ul>
</td></tr>
  </table>
  </dd>
</dl>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a33590324368a1f1140dc68faf8049fca" title="Accessor of the motion channel of the retina (models peripheral vision). ">getMagnoRAW</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a33590324368a1f1140dc68faf8049fca">◆ </a></span>getMagnoRAW() <span class="overload">[1/2]</span></h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::getMagnoRAW </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>retinaOutput_magno</em></td><td>)</td>
          <td></td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retinaOutput_magno</td><td>=</td><td>cv.bioinspired_Retina.getMagnoRAW(</td><td class="paramname">[, retinaOutput_magno]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.bioinspired_Retina.getMagnoRAW(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>Accessor of the motion channel of the retina (models peripheral vision). </p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#ad8ec45e39a333eeb759e0925357f4ec5" title="Accessor of the motion channel of the retina (models peripheral vision). ">getMagno</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a5185329f03228f9427481afaff0e29bb">◆ </a></span>getMagnoRAW() <span class="overload">[2/2]</span></h2>
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          <td class="memname">virtual const <a class="el" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> cv::bioinspired::Retina::getMagnoRAW </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retinaOutput_magno</td><td>=</td><td>cv.bioinspired_Retina.getMagnoRAW(</td><td class="paramname">[, retinaOutput_magno]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.bioinspired_Retina.getMagnoRAW(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a1a6a151832812c2b276e5cb244f7a544">◆ </a></span>getOutputSize()</h2>
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          <td class="memname">virtual <a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> cv::bioinspired::Retina::getOutputSize </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.bioinspired_Retina.getOutputSize(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>Retreive retina output buffer size that can be different from the input if a spatial log transformation is applied. </p>
<dl class="section return"><dt>Returns</dt><dd>the retina output buffer size </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#ada6dac13985015a01a461b5cde177e95">◆ </a></span>getParameters()</h2>
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          <td class="memname">virtual <a class="el" href="../../d2/df5/structcv_1_1bioinspired_1_1RetinaParameters.html">RetinaParameters</a> cv::bioinspired::Retina::getParameters </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
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<dl class="section return"><dt>Returns</dt><dd>the current parameters setup </dd></dl>
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<a id="a89bbd0119f52b9936cabdfba97561c0f"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a89bbd0119f52b9936cabdfba97561c0f">◆ </a></span>getParvo()</h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::getParvo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>retinaOutput_parvo</em></td><td>)</td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retinaOutput_parvo</td><td>=</td><td>cv.bioinspired_Retina.getParvo(</td><td class="paramname">[, retinaOutput_parvo]</td><td>)</td></tr></table>
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<p>Accessor of the details channel of the retina (models foveal vision). </p>
<p>Warning, getParvoRAW methods return buffers that are not rescaled within range [0;255] while the non RAW method allows a normalized matrix to be retrieved.</p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">retinaOutput_parvo</td><td>the output buffer (reallocated if necessary), format can be :<ul>
<li>a <a class="el" href="../../d3/d63/classcv_1_1Mat.html" title="n-dimensional dense array class ">Mat</a>, this output is rescaled for standard 8bits image processing use in OpenCV</li>
<li>RAW methods actually return a 1D matrix (encoding is R1, R2, ... Rn, G1, G2, ..., Gn, B1, B2, ...Bn), this output is the original retina filter model output, without any quantification or rescaling. </li>
</ul>
</td></tr>
  </table>
  </dd>
</dl>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#ab8bb17543b78ef9d32be3a4619d2b2dd" title="Accessor of the details channel of the retina (models foveal vision). ">getParvoRAW</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#ab8bb17543b78ef9d32be3a4619d2b2dd">◆ </a></span>getParvoRAW() <span class="overload">[1/2]</span></h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::getParvoRAW </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>retinaOutput_parvo</em></td><td>)</td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retinaOutput_parvo</td><td>=</td><td>cv.bioinspired_Retina.getParvoRAW(</td><td class="paramname">[, retinaOutput_parvo]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.bioinspired_Retina.getParvoRAW(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>Accessor of the details channel of the retina (models foveal vision). </p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a89bbd0119f52b9936cabdfba97561c0f" title="Accessor of the details channel of the retina (models foveal vision). ">getParvo</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a12f3b934dc029c81d733007b27322534">◆ </a></span>getParvoRAW() <span class="overload">[2/2]</span></h2>
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          <td class="memname">virtual const <a class="el" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> cv::bioinspired::Retina::getParvoRAW </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retinaOutput_parvo</td><td>=</td><td>cv.bioinspired_Retina.getParvoRAW(</td><td class="paramname">[, retinaOutput_parvo]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.bioinspired_Retina.getParvoRAW(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a80d39a3463c206425e16ce85caa78d03">◆ </a></span>printSetup()</h2>
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          <td class="memname">virtual const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> cv::bioinspired::Retina::printSetup </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
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<p>Outputs a string showing the used parameters setup. </p>
<dl class="section return"><dt>Returns</dt><dd>a string which contains formated parameters information </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a9d18358b520c4dd7931a9154cc053649">◆ </a></span>run()</h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::run </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>inputImage</em></td><td>)</td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.bioinspired_Retina.run(</td><td class="paramname">inputImage</td><td>)</td></tr></table>
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<p>Method which allows retina to be applied on an input image,. </p>
<p>after run, encapsulated retina module is ready to deliver its outputs using dedicated acccessors, see getParvo and getMagno methods </p><dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">inputImage</td><td>the input <a class="el" href="../../d3/d63/classcv_1_1Mat.html" title="n-dimensional dense array class ">Mat</a> image to be processed, can be gray level or BGR coded in any format (from 8bit to 16bits) </td></tr>
  </table>
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<h2 class="memtitle"><span class="permalink"><a href="#aa66dca22cadf9293164bef39f3690a94">◆ </a></span>setColorSaturation()</h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::setColorSaturation </td>
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          <td class="paramtype">const bool </td>
          <td class="paramname"><em>saturateColors</em> = <code>true</code>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>colorSaturationValue</em> = <code>4.0f</code> </td>
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          <td></td>
          <td>)</td>
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<p>Activate color saturation as the final step of the color demultiplexing process -&gt; this saturation is a sigmoide function applied to each channel of the demultiplexed image. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">saturateColors</td><td>boolean that activates color saturation (if true) or desactivate (if false) </td></tr>
    <tr><td class="paramname">colorSaturationValue</td><td>the saturation factor : a simple factor applied on the chrominance buffers </td></tr>
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<h2 class="memtitle"><span class="permalink"><a href="#a741fc44059111f3e2d5ba6ab1fa1d907">◆ </a></span>setup() <span class="overload">[1/3]</span></h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::setup </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> </td>
          <td class="paramname"><em>retinaParameterFile</em> = <code>""</code>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const bool </td>
          <td class="paramname"><em>applyDefaultSetupOnFailure</em> = <code>true</code> </td>
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          <td>)</td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.bioinspired_Retina.setup(</td><td class="paramname">[, retinaParameterFile[, applyDefaultSetupOnFailure]]</td><td>)</td></tr></table>
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<p>Try to open an XML retina parameters file to adjust current retina instance setup. </p>
<ul>
<li>if the xml file does not exist, then default setup is applied</li>
<li>warning, Exceptions are thrown if read XML file is not valid <dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">retinaParameterFile</td><td>the parameters filename </td></tr>
    <tr><td class="paramname">applyDefaultSetupOnFailure</td><td>set to true if an error must be thrown on error</td></tr>
  </table>
  </dd>
</dl>
You can retrieve the current parameters structure using the method <a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#ada6dac13985015a01a461b5cde177e95">Retina::getParameters</a> and update it before running method <a class="el" href="../../dc/d54/classcv_1_1bioinspired_1_1Retina.html#a741fc44059111f3e2d5ba6ab1fa1d907" title="Try to open an XML retina parameters file to adjust current retina instance setup. ">Retina::setup</a>. </li>
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<h2 class="memtitle"><span class="permalink"><a href="#a75ee531b20e2c32892773625de5ecdb1">◆ </a></span>setup() <span class="overload">[2/3]</span></h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::setup </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../da/d56/classcv_1_1FileStorage.html">cv::FileStorage</a> &amp; </td>
          <td class="paramname"><em>fs</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const bool </td>
          <td class="paramname"><em>applyDefaultSetupOnFailure</em> = <code>true</code> </td>
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<p>This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. </p><dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">fs</td><td>the open Filestorage which contains retina parameters </td></tr>
    <tr><td class="paramname">applyDefaultSetupOnFailure</td><td>set to true if an error must be thrown on error </td></tr>
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<h2 class="memtitle"><span class="permalink"><a href="#ac9f944965a104c355467628b07eaf887">◆ </a></span>setup() <span class="overload">[3/3]</span></h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::setup </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../d2/df5/structcv_1_1bioinspired_1_1RetinaParameters.html">RetinaParameters</a> </td>
          <td class="paramname"><em>newParameters</em></td><td>)</td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.bioinspired_Retina.setup(</td><td class="paramname">[, retinaParameterFile[, applyDefaultSetupOnFailure]]</td><td>)</td></tr></table>
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<p>This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. </p><dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">newParameters</td><td>a parameters structures updated with the new target configuration. </td></tr>
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<h2 class="memtitle"><span class="permalink"><a href="#acfec2a2bef33e6ef73a38576f645278b">◆ </a></span>setupIPLMagnoChannel()</h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::setupIPLMagnoChannel </td>
          <td>(</td>
          <td class="paramtype">const bool </td>
          <td class="paramname"><em>normaliseOutput</em> = <code>true</code>, </td>
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          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>parasolCells_beta</em> = <code>0.f</code>, </td>
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          <td class="paramkey"></td>
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          <td class="paramtype">const float </td>
          <td class="paramname"><em>parasolCells_tau</em> = <code>0.f</code>, </td>
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          <td class="paramtype">const float </td>
          <td class="paramname"><em>parasolCells_k</em> = <code>7.f</code>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>amacrinCellsTemporalCutFrequency</em> = <code>1.2f</code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>V0CompressionParameter</em> = <code>0.95f</code>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>localAdaptintegration_tau</em> = <code>0.f</code>, </td>
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          <td class="paramkey"></td>
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          <td class="paramtype">const float </td>
          <td class="paramname"><em>localAdaptintegration_k</em> = <code>7.f</code> </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.bioinspired_Retina.setupIPLMagnoChannel(</td><td class="paramname">[, normaliseOutput[, parasolCells_beta[, parasolCells_tau[, parasolCells_k[, amacrinCellsTemporalCutFrequency[, V0CompressionParameter[, localAdaptintegration_tau[, localAdaptintegration_k]]]]]]]]</td><td>)</td></tr></table>
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<p>Set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel. </p>
<p>this channel processes signals output from OPL processing stage in peripheral vision, it allows motion information enhancement. It is decorrelated from the details channel. See reference papers for more details.</p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">normaliseOutput</td><td>specifies if (true) output is rescaled between 0 and 255 of not (false) </td></tr>
    <tr><td class="paramname">parasolCells_beta</td><td>the low pass filter gain used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), typical value is 0 </td></tr>
    <tr><td class="paramname">parasolCells_tau</td><td>the low pass filter time constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is frame, typical value is 0 (immediate response) </td></tr>
    <tr><td class="paramname">parasolCells_k</td><td>the low pass filter spatial constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is pixels, typical value is 5 </td></tr>
    <tr><td class="paramname">amacrinCellsTemporalCutFrequency</td><td>the time constant of the first order high pass fiter of the magnocellular way (motion information channel), unit is frames, typical value is 1.2 </td></tr>
    <tr><td class="paramname">V0CompressionParameter</td><td>the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 0.95 </td></tr>
    <tr><td class="paramname">localAdaptintegration_tau</td><td>specifies the temporal constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation </td></tr>
    <tr><td class="paramname">localAdaptintegration_k</td><td>specifies the spatial constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation </td></tr>
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<h2 class="memtitle"><span class="permalink"><a href="#ac6d6767e14212b5ebd7c5bbc6477fa7a">◆ </a></span>setupOPLandIPLParvoChannel()</h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::setupOPLandIPLParvoChannel </td>
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          <td class="paramname"><em>colorMode</em> = <code>true</code>, </td>
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          <td></td>
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          <td class="paramname"><em>photoreceptorsLocalAdaptationSensitivity</em> = <code>0.7f</code>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>photoreceptorsTemporalConstant</em> = <code>0.5f</code>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>photoreceptorsSpatialConstant</em> = <code>0.53f</code>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>horizontalCellsGain</em> = <code>0.f</code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>HcellsTemporalConstant</em> = <code>1.f</code>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>HcellsSpatialConstant</em> = <code>7.f</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const float </td>
          <td class="paramname"><em>ganglionCellsSensitivity</em> = <code>0.7f</code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.bioinspired_Retina.setupOPLandIPLParvoChannel(</td><td class="paramname">[, colorMode[, normaliseOutput[, photoreceptorsLocalAdaptationSensitivity[, photoreceptorsTemporalConstant[, photoreceptorsSpatialConstant[, horizontalCellsGain[, HcellsTemporalConstant[, HcellsSpatialConstant[, ganglionCellsSensitivity]]]]]]]]]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Setup the OPL and IPL parvo channels (see biologocal model) </p>
<p>OPL is referred as Outer Plexiform Layer of the retina, it allows the spatio-temporal filtering which withens the spectrum and reduces spatio-temporal noise while attenuating global luminance (low frequency energy) IPL parvo is the OPL next processing stage, it refers to a part of the Inner Plexiform layer of the retina, it allows high contours sensitivity in foveal vision. See reference papers for more informations. for more informations, please have a look at the paper Benoit A., Caplier A., Durette B., Herault, J., "USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING", Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: <a href="http://dx.doi.org/10.1016/j.cviu.2010.01.011">http://dx.doi.org/10.1016/j.cviu.2010.01.011</a> </p><dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">colorMode</td><td>specifies if (true) color is processed of not (false) to then processing gray level image </td></tr>
    <tr><td class="paramname">normaliseOutput</td><td>specifies if (true) output is rescaled between 0 and 255 of not (false) </td></tr>
    <tr><td class="paramname">photoreceptorsLocalAdaptationSensitivity</td><td>the photoreceptors sensitivity renage is 0-1 (more log compression effect when value increases) </td></tr>
    <tr><td class="paramname">photoreceptorsTemporalConstant</td><td>the time constant of the first order low pass filter of the photoreceptors, use it to cut high temporal frequencies (noise or fast motion), unit is frames, typical value is 1 frame </td></tr>
    <tr><td class="paramname">photoreceptorsSpatialConstant</td><td>the spatial constant of the first order low pass filter of the photoreceptors, use it to cut high spatial frequencies (noise or thick contours), unit is pixels, typical value is 1 pixel </td></tr>
    <tr><td class="paramname">horizontalCellsGain</td><td>gain of the horizontal cells network, if 0, then the mean value of the output is zero, if the parameter is near 1, then, the luminance is not filtered and is still reachable at the output, typicall value is 0 </td></tr>
    <tr><td class="paramname">HcellsTemporalConstant</td><td>the time constant of the first order low pass filter of the horizontal cells, use it to cut low temporal frequencies (local luminance variations), unit is frames, typical value is 1 frame, as the photoreceptors </td></tr>
    <tr><td class="paramname">HcellsSpatialConstant</td><td>the spatial constant of the first order low pass filter of the horizontal cells, use it to cut low spatial frequencies (local luminance), unit is pixels, typical value is 5 pixel, this value is also used for local contrast computing when computing the local contrast adaptation at the ganglion cells level (Inner Plexiform Layer parvocellular channel model) </td></tr>
    <tr><td class="paramname">ganglionCellsSensitivity</td><td>the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 0.7 </td></tr>
  </table>
  </dd>
</dl>
</div>
</div>
<a id="a92d80a2c309c46a46b22ec125cad3943"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a92d80a2c309c46a46b22ec125cad3943">◆ </a></span>write() <span class="overload">[1/2]</span></h2>
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          <td class="memname">virtual void cv::bioinspired::Retina::write </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> </td>
          <td class="paramname"><em>fs</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.bioinspired_Retina.write(</td><td class="paramname">fs</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Write xml/yml formated parameters information. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">fs</td><td>the filename of the xml file that will be open and writen with formatted parameters information </td></tr>
  </table>
  </dd>
</dl>
</div>
</div>
<a id="af0fb1fda44face9993785ef41b38430d"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af0fb1fda44face9993785ef41b38430d">◆ </a></span>write() <span class="overload">[2/2]</span></h2>
<div class="memitem">
<div class="memproto">
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  <td class="mlabels-left">
      <table class="memname">
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          <td class="memname">virtual void cv::bioinspired::Retina::write </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &amp; </td>
          <td class="paramname"><em>fs</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.bioinspired_Retina.write(</td><td class="paramname">fs</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. </p>
<p>Reimplemented from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a1f8ad7b8add515077367fb9949a174d2">cv::Algorithm</a>.</p>
</div>
</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li>opencv2/bioinspired/<a class="el" href="../../d5/d40/retina_8hpp.html">retina.hpp</a></li>
</ul>
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